Abstract
The large-scale deployment of smart home technologies will unlock the flexibility of prosumers, which in turn will be transformed into electricity market services by aggregators. This paper proposes a new network-constrained bidding optimization strategy to coordinate the participation of aggregators of prosumers in the day-ahead energy and secondary reserve markets. This bidding optimization strategy consists of a decentralized approach based on the alternating direction method of multipliers, where aggregators negotiate with the distribution system operator to obtain network-constrained energy and secondary reserve bids. For a case study of 2 aggregators and 1 distribution system operator, the results show that the network-constrained bidding strategy computes cost-effective and network-feasible energy and secondary reserve bids, as opposed to a network-free bidding strategy. In addition, the network-constrained bidding strategy preserves the independent roles of aggregators and the distribution system operator, and the data privacy of all agents.

Abstract
Over the past few decades, much has been done globally to make final energy consumption more sustainable, integrating more renewable resources. In Europe, there are many directives and regulations that imposes to the states ambitious targets on the promotion of renewable energies and energetic efficiency among others. Portugal has not only fulfilled all the goals but has also exceeded them. This is the case with the integration of renew ables in electricity consumption, which is currently rated at 53 %, with the prospect of reaching 80% in 2030. In this scenario, it is important to encourage the energy production from the solar resource as the country has optimal conditions for this purpose. This research assess the existing Portuguese potential for floating photovoltaic systems and its integration in the power grid. Another aim of this study is to sizing and assesses the energetic potential of floating solar power plant in Gouvaes dam, included in the Tamega hydroelectric complex in under construction in northern Portugal belong to Iberdrola Company.

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With the implementation of micro grids and smart grids, new business models able to cope with the new opportunities are being developed. Virtual Power Players are a player that allows aggregating a diversity of entities, to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. This paper proposes methodologies to develop strategic remuneration of aggregated consumers with demand response participation, this model uses a clustering algorithm, applied on values that were obtained from a scheduling methodology of a real Portuguese distribution network with 937 buses, 20310 consumers and 548 distributed generators. The normalization methods and clustering methodologies were applied to several variables of different consumers, which creates sub-groups of data according to their correlations. The clustering process is evaluated so that the number of data sub-groups that brings the most added value for the decision-making process is found, according to players characteristics. © Springer Nature Switzerland AG 2020.

Abstract
One important goal of the climate commitment in the European Union (EU) is to reduce primary energy demand in the transport sector and increase the use of renewables, since around 33% of primary energy is consumed in this sector. Therefore, the EU ordered its member states to raise the number of electric vehicles (EVs) within Europe. Consequently, the energy demand for electricity will rise as a function of the number of EVs. To avoid local grid overload and guarantee a higher percentage of clean energy, EV charging stations can be supported by a combined system of grid-connected photovoltaic modules and battery storage. In this paper, the focus lies on the feasibility and economic aspects of such systems. To provide an overview of the different e-charging station combinations, a support tool was modelled and developed, making it possible to size and manage EVs charging stations with only a few input parameters. Thanks to its easy handling, the tool suits a wide spectrum of users. Due to enhanced optional settings, this tool is suitable for detailed input parameters for professionals as well. Input categories are basically divided into the photovoltaic (PV) system, battery storage, the charging station itself, and investment analysis. The tool supports decisions for solar charging stations designed for different parking locations like offices, schools, and public and private places.

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